Method and system for applying data retention policies in a computing platform

ABSTRACT

Systems and methods for a multitenant computing platform. Original data is generated through operation of a computing platform system on behalf of an account of the computing platform system, and the original data is moderated according to a data retention policy set for the account. The moderated data is stored at the computing platform system. The computing platform system moderates the generated data by securing sensitive information of the generated data from access by the computing platform system, and providing operational information from the generated data. The operational information is accessible by the computing platform system during performance of system operations.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.14/793,435, filed 7-Jul.-2015, which claims the benefit of U.S.Provisional Application Ser. No. 62/021,645, filed on 7-Jul.-2014, bothof which are incorporated in their entirety by this reference.

TECHNICAL FIELD

This invention relates generally to the data management field, and morespecifically to a new and useful method and system for applying dataretention policies in the data management field.

BACKGROUND

Data analytics are an important part of running a data driven computingplatform. However, there are many cases where the data is inappropriatefor storage. In some cases, the information is sensitive and an operatorwould not want to store such information. Storing such information mayviolate the trust of involved parties or create an informationliability. In some cases, the data cannot be stored to maintaincompliance with regulations. For example, personal medical informationmay not be allowed to be stored when building a HIPAA compliantapplication. Thus, there is a need in the data management field tocreate a new and useful method and system for applying data retentionpolicies in a computing platform. This invention provides such a new anduseful method and system.

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1 is a flow diagram of a method of a preferred embodiment;

FIG. 2 is a schematic representation of an exemplary implementation of apreferred embodiment;

FIG. 3 is a schematic representation of an exemplary implementation of apreferred embodiment;

FIG. 4 is a flow diagram of a method of a preferred embodiment;

FIG. 5 is a flow diagram of a method of a preferred embodiment; and

FIG. 6 is an architecture diagram of system of a preferred embodiment.

DESCRIPTION OF THE PREFERRED EMBODIMENTS

The following description of preferred embodiments of the invention isnot intended to limit the invention to these preferred embodiments, butrather to enable any person skilled in the art to make and use thisinvention.

1. Method

As shown in FIG. 1, a method for controlling data of a preferredembodiment can include setting of a data retention policy of an accountS110, generating data through the operation of a computing platformS120, moderating data of the account according to the data retentionpolicy of the account S130, and storing the moderated data S140. Themethod functions to provide a mechanism through which a data-drivencomputing platform can accommodate a wide variety of data retentionpolices while serving number of different accounts. The method may beused to define how data is stored long term. Additionally oralternatively, the method may be used to provide data “deletion”capabilities to an account wherein the operational significance of thedata is preserved for other parties (e.g., a computing platformoperator). The method is preferably used in a multitenant computingplatform, wherein each account, sub-account or other data scope may haveindividually assigned data retention polices.

The computing platform is preferably data-driven in the sense that theaccumulation of data is used in subsequent processes of the platform—atleast one operational aspect depends on accurate and exhaustivecollection of data. In one case the data of the computing platform ismetered/measured for each account and used in regulating usage of anaccount. In computing platform where the usage is a factor of billing,the data history for an account must be accurate to calculate fees. Oneobjective of the method is to enable such data-driven behavior, whilesimultaneously enabling data protection that may otherwise conflict withthe notion of metering usage.

In one particular implementation, the computing platform is acommunication platform and more specifically a communication applicationplatform such as the one described in U.S. Pat. No. 8,306,021, issued6-Nov.-2012, which is incorporated in its entirety by this reference. Acommunication platform may have complicated billing models that candepend on the count of communications, the source and/or destination ofcommunication, the type of communication, the duration of communication,the events and media processes associated with the communication (e.g.,text to speech services, speech detection services, transcriptionservices, recording services, etc.), rate and threshold billingvariables, and other suitable factors. Such complicated billing modelsmay preclude the on-demand calculation of itemized billing percommunication or data record. The method can address the requirement ofaccounting while preserving the data in a private manner. Herein, thecommunication platform may be used as an exemplary platform, but anysuitable computing platform may similarly apply the method forcontrolling data.

Block S110, which includes setting of a data retention policy of anaccount S110, functions to receive a signal that defines how at least asubset of data should be retained with the system. A data retentionpolicy is preferably set by an account holder. The data retention policyis preferably received from the account holder. In one variation, thedata retention policy is pre-defined. The policy retention policy couldbe globally pre-set for all data generated in association with theaccount. The policy retention policy may alternatively be defined for asub-set of account data. For example, a policy retention policy may bemapped to a sub-account of the account, to a type of data (e.g., datagenerated during a voice communication or data generated during amessage communication), or any suitable data scope. For example, dataassociated with SMS and MMS messaging may not be set for “deletion”while voice communication data is kept in an original format. Similarly,the data retention policy for communication with a first endpoint (e.g.,phone number) may be different for data retention policies for a secondendpoint. In one variation, an administrator of an account may specifythe data retention policy/policies through an administrator controlpanel user interface. In another variation, the data retention policymay be set in response to a developer API request. A data retentionpolicy may alternatively be defined in any suitable manner.

Data retention policy may additionally or alternatively be specifiedon-demand. The data retention policy can be defined in directives duringoperation of the computing platform. In the communication platformimplementation, a data retention policy may be selectively changed forpart or all of a call. The data retention policy directives may providecommands to initiate pause, end, or otherwise change the data retentionpolicy. A data retention policy may be initiated in a first instance andthen terminated in a second instance. Any data generated or associatedwith the time period between the first and second instances ispreferably processed according to the data retention policy. Dataoutside of those two instances may be processed according to the defaultdata retention policy or any original data retention policy. In oneexample, a user may be placing a call to a banking customer supportphone system. While most of the communicated information is notsensitive data, a portion of the call may require the customer to enterpersonal information such as a credit card. The data retention policymay be elevated to a higher level of data protection during this processto prevent such data being retained and accessible in data logs.

Additionally or alternatively, a specific request to apply dataretention to one or more data elements may be received and processed. Inthis variation, specific data records can be selectively targeted forparticular data retention policy compliance.

A data retention policy preferably defines actions to take on data priorto storing or warehousing the data. In one variation, there arepreferably at least two data retention policies. A first data retentionpolicy is a passive data retention policy that preserves the data in anoriginal and raw format. Such a data retention policy is preferably adefault data retention policy, and no action is preferably taken on thedata. The passive data retention policy can alternatively be describedas a lack of a data retention policy. The other forms of data retentionpolicy are preferably transformative data retention policies that resultin some change or transformation of the data. A transformative dataretention policy preferably removes or secures sensitive informationwhile creating some mechanism through which the computing platform canaccomplish data-driven operations.

A transformative data retention policy will preferably take some form ofa data retention action on the data during moderation of the data. Adata retention action can include data redaction/censoring, dataclassifying/bucketing, data aggregating, data encryption, partialdeletion, and/or any suitable approach to data protection. Within thecomputing platform varying levels of data retention policies may bedefined wherein different levels of data retention may have differingdegrees of data destruction/preservation. Additionally, different formsof data transformation may be applied to different data fields. In acomputing platform, the data stored may follow a substantially definedschema and the forms of transformations that should be applied can becustomized for each field. For example, some fields may not be used fordata-driven processes and can be deleted, while other fields may besuitable for a form of redaction, while other fields may be bettersuited for data classifying or bucketing.

A transformative data retention policy may additionally include one ormore defined temporal properties. One temporal property may define howlong the data may be retained before the data is moderated andtransformed. One account may maintain the original raw data for 30 daysand after 30 days transform the data. Another account may have notemporary need for the data and transform data directly after completingactive use (e.g., during initial warehousing of the data). A secondtemporal property may be a backup time window that defines how long theoriginal data is preserved in addition to the transformed data beforedeletion. In this variation, the method enables the capability to undoor reverse the transformation of a data retention policy. For example, abackup time window property for one account of 24 hours will allow anydata transformation or deletion request to be undone for up to 24 hours.In one implementation, deleted or transformed data may be shown in aspecial folder within an administrator control panel until the timewindow is up. In another example, a backup time window property foranother account can be set to zero seconds, and any data transformationsor deletion requests are effective immediately and cannot be reversed.

The interface through which a data retention policy is received can bethrough an Application Program Interface, a configuration file, a userinterface (e.g., in an administrator control panel), or any suitableinterface. The manner in which a data retention policy is defined may beachieved through various approaches. In a first variation, atransformative data retention policy can be selected from a set ofoffered transformative data retention policy options. For example, anaccount may be able to set up an application within a communicationapplication platform, and in the settings of that application select adefault of no data transformations, a pre-defined redaction process, ora custom encryption data retention process. In another variation, a dataretention policy may be specifically defined. A schema or configurationfile may be provided that defines how data retention should be applied.The data retention can be specified specifically for different dataattributes. Particular types of data retention actions may be directedto particular data types, data conditions (e.g., if a data fieldsatisfies a specified condition enact a data retention action), datafields, or other suitable aspects. Alternatively, any suitable approachmay be used to define the data retention policy. In another variation,the type of data retention policy may be defined based on the type ofaccount.

Block S120, which includes generating data through the operation of acomputing platform S120, functions to produce data within a system. Thedata produced is preferably data produced as a result of the accounts,users, or other entities using the multi-tenant computing platform. Thedata can be data logs, API request/response records, captured packets(PCAP files), form data input, user generated data, generated orobtained media (e.g., audio, images, video, etc.), and/or any suitabletype of data. The data may be accessible to an account holder for anysuitable use. For example, a customer support phone system built in acommunication application platform may include event logs that includemeta data about the calling phone number, the called phone number, theduration of the call, media recordings made during the call, DTMF input,and other suitable information. An account holder is preferably adeveloper account or administrator account, which may build differentanalytics or tools that leverage a portion of the generated data. Forexample, a history of a customer support agent could be generated bypolling the data source of the communication application platform. Sincethe computing platform may be built as a general set of functionality toserve a wide variety of parties, there may be particular use cases towhich this data logging behavior is not ideal or possibly prohibitive.For example, if phone system builds a tool where users enter theirsocial security number, the data logs will automatically create a recordof callers' social security numbers. The administrator of this systemmay not want to be liable for having access to such sensitive data. Inanother example, a health care system may end up storing personalidentifiable information in the data, which may cause HIPAA complianceissues and so such automatic data logging may ordinarily prevent such ause case. The method of the preferred embodiment can preferably addresssuch scenarios.

While the data generated may be the result of building a generic tool,the computing platform may additionally partially depend on informationof the data. The computing platform in which the data is generated maybe an at least partially closed system with operations that are outsideof the control or direction of an account holder—there are preferablycomponents of the computing platform to which an account holder/user ofthe platform will not have visibility. The computing platform ispreferably multitenant, wherein multiple account holders will share theuse of the computing platform while maintaining distinct andsubstantially independent applications/services. The partially closedportions of the platform can include the system orchestration system,usage/analytics tools, billing engine, business intelligence tools, aplatform operations system (e.g., the platform operations system 270 ofFIG. 2) and/or any suitable system. In some implementations, theplatform operations system performs at least one of platformorchestration, usage metering, analytics, billing, and businessintelligence. In some implementations, the platform operations systemperforms usage/analytics. Such system (or systems) can depend on thedata generated in connection with an account holder. The data retentionpolicy management method described herein may function to enable dataprotection without hindering or preventing such operations.

The data generated may have different stages in the data life cycle. Thedata is preferably generated as a result of some event relating to anaccount, sub-account, user action of an application, service action, orother suitable event. The data may have a period of being in-flightwherein inflight data is actively stored for use within some operation.For example, data generated during a phone call may be in-flight for theduration of the call. An SMS or MMS message may have in-flight data forthe duration to complete transmission. Alternatively, there may be aconcept of a conversation wherein the data is in-flight for the durationof the messaging conversation. After active use, the data may be movedto a temporary storage system prior to being transmitted for datawarehousing. Data warehousing will preferably be used to store the datafor long duration. It is between in-flight state and the datawarehousing that blocks S130 preferably occurs, but Block S130 mayalternatively occur at any suitable time. The data may additionally oralternatively include any alternative states.

Block S130, which includes moderating data of the account according tothe data retention policy of the account, functions to exercise theactions defined by the data retention policy. As described above, thedata retention policy is preferably exercised after active use and priorto long term storage for data records. The data retention policy mayalternatively be applied to any new data records at a periodic interval,be applied immediately as data is generated, or at any suitable time.The conditions in which the data retention policy is exercised arepreferably dependent on the data retention policy configuration of anaccount. More generally, the moderation of the data depends on the dataretention policy defined for the data scope (e.g., sub-account data,user data, etc.). In the case where the data retention policy is to takeno action, then the data is preferably stored in a raw and unalteredstate. In the case where the data retention policy is a transformativedata retention policy, the data will be augmented according to thedefined actions. There may be different variations on how data isaugmented or moderated. Some preferred variations might include dataredaction processing, data classifying, data aggregating, dataencrypting, partially deleting, and/or any suitable approach to dataprotection.

Redaction processing functions to remove elements of the data that aresensitive. The redaction processing can effectively censor data so as toput it in a form suitable for storage. Redaction processing additionallycan preserve a subset of the data content. Preferably, the informationin the data that is desired by the computing platform can be preservedwhile a subset or all of the remaining data is removed. Redactionprocessing is preferably applied to data fields or properties where thesemantics or pattern of the data is understood sufficiently todifferentiate between what should be kept and what should be removed. Inone case, phone numbers may be an element of a data record. Phonenumbers may provide personally identifying information as they often mapback to an individual. However, a communication platform may depend onknowing the country and area codes of phone numbers during billing of anaccount. Accordingly, the country and area code are preferably preservedwhile the remaining four digits are censored. In one variation,redaction processing may include automatically detecting a pattern andapplying censorship to the pattern. Automatic detection may be useful insituations where a fixed rule cannot be defined to specify where andwhen content will need to be augmented. Credit card numbers, socialsecurity numbers, and account numbers, addresses, and other suitableforms of information may be detected and automatically removed from thedata. Such type of content may appear in various places, when datamatches those patterns it may be automatically removed.

Data classifying functions to abstract or bucket the data content toremove details of the original information. The data classifyingpreferably includes abstracting up the level of information in theoriginal data. One approach is to classify content into a higher-levelabstraction. For example, geo-location data may be generalized fromprecise geo-location data to general location information such as zipcode, region, city, state or country. As another alternative, datametrics may be bucketed from precise measurements into ranges. Forexample, a data metric measuring the duration of a call may be changedfrom second-level precision to minute level precision.

Data aggregating functions to create a distinct data record that is thecumulative combination of previous data records. The precise metrics ofa data record can be maintained but only in combination with a set ofother data records. The individual metric is preferably deleted orcensored. For example, the total duration of a phone call may beaggregated into total duration of all phone calls for an account,however the duration of the individual call cannot normally be obtained.

Encrypting data functions to cryptographically transform the data.Encrypting data preferably depends on an account-defined key. Encryptingdata preferably includes receiving an encryption callback reference,determining the data content to be encrypted, transmitting the originalcontent to the encryption callback reference (e.g., the encryptioncallback 281 of FIG. 2), receiving encrypted data content and using theencrypted data content in place of the original content. The encryptioncallback reference is preferably a callback URI operated by the accountholder. HTTP, SPDY, or any suitable application layer protocol may beused to communicate the original data to the callback URI. The accountholder will receive the original data and can use a self-definedencryption algorithm and key to encrypt the data, which is then returnedfor storage. The encryption allows only the account holder to access thecontents of the data. Encryption can be used if the data should besecured but not deleted permanently. Encryption may be used incombination with redaction classification, aggregation, or any suitabledata transformation. Redaction, classification, and aggregation mayenable system dependent information to be preserved while removingsensitive data. For example, if phone numbers are encrypted, the accountholder may be able to decrypt the encrypted version to view the data.However, since a communication application platform may depend on thecountry and area code of that data, a redacted copy of that dataproperty may additionally be stored.

A data augmentation may additionally include a partial deletion of data,wherein some data fields or whole data records may be deleted. Somesubset of data types or data parameters may be fully deletable. Suchfields may include customer defined data fields (e.g., data tags ormetadata).

Block S140, which includes storing the moderated data, functions tostore the moderated data. The moderated data can be stored in anysuitable manner. As described above, for encrypted data. A second formof data transformation may be stored for some all parts of the encrypteddata. The stored moderated data may be used for various systemoperations such as scaling infrastructure, metering account usage,billing for account usage, informing business decisions, acquiringassets, or any suitable data-driven decision. The policy transformeddata is preferably applied to any location where data is stored such asin a data warehouse, log files, media records, and/or any suitablelocation.

The method can additionally facilitate various data relatedfunctionality. Such functionality may be enabled on secured data despitethe original data being too sensitive to normally allow suchfunctionality. As a primary functionality, account usage and analyticscan be provided. Data aggregation, classification, and selectiveredaction can preserve some level of information that can provideinsight into patterns. Such data preservation may additionally beapplied to enable fraud detection, error detection, or general eventpattern detection. Within the computing platform, the data informationmay be used in making decisions related to platform administration,orchestrating a cluster or distributed computing system,allocating/deallocating resource, pricing, and/or other operationalfactors of the computing platform. The systematic approach to dataretention policies may additionally provide an audit trail of datamanagement for an account, which can be used to show data compliance invarious situations.

In one preferred implementation, the method is applied to acommunication platform that can facilitate synchronous communicationsuch as voice, video, screen sharing, virtual reality and/or anysuitable media stream. The synchronous communication may use PSTN, SIP,WebRTC, IP-based protocols, or any suitable communication protocols. Thecommunication platform may additionally or alternatively facilitateasynchronous communication such as SMS, MMS, or IP based messaging. Asshown in FIG. 2, a communication (e.g., a communication requested by thecommunication request 211 of FIG. 2) will be executed on thecommunication platform (e.g., by the communication system 210 of FIG.2). Various events during the communication such as the communicationrequest, media generated during the communication, input received duringthe communication (e.g., DTMF input), and a summary of the communicationafter it completes may all be exemplary data records generated (e.g., bythe communication system 210 of FIG. 2) in association with thecommunication. While the communication is active, the data is preferablystored in in-flight data storage (e.g., the in-flight data storage 220of FIG. 2) (e.g., active data storage). Data may be mutable and possiblyincomplete at this state. Once the call is completed, the associateddata may be moved to a post-flight data storage system (e.g., thepost-flight data storage 230 of FIG. 2). The post-flight data storagefunctions as a temporary data storage solution prior to being moved to adata warehousing solution (e.g., the data warehouse system 260 of FIG.2). The post flight data storage may additionally provide fasterreal-time data information for particular use-cases. Periodically (basedon a time period or satisfying some condition), the post-flight data isonboarded into the data warehousing system (e.g., the data warehousesystem 260 of FIG. 2). A data retention policy engine (e.g., the dataretention policy engine 251 of the data manager 250 of FIG. 2)preferably facilitates the onboarding process by exercising dataretention policies (e.g., the data retention policy 252 of FIG. 2) thatare assigned to the various data records. Data for an account that lacksa defined data retention policy will be onboarded with notransformation. Data for an account that has a transformation dataretention policy will be transformed according to the data retentionpolicy.

In one example, form of a data retention policy a call record may havethe following actions applied call record fields: the “to” field isredacted to exclude last four digits, the “from” field is redacted toexclude last four digits, application URL field is deleted, durationfield is bucketed into five minute buckets, time field is bucketed toonly show events by hour, associated account identifier is kept, and aprice field is deleted or bucketed. A location field may be abstractedto only show city information. Call recordings may be deleted orencrypted through an account controlled cryptographic key.

In some implementations, the communication platform includes thecommunication system 210, the in-flight data storage 220, thepost-flight data storage 230, the data manager 250, the data retentionpolicy engine 251, the data warehouse 260, the data retention policy252, and the platform operations system 270, and the account holdersystem 280 is external to the communication platform.

In some implementations, the communication platform (e.g., thecommunication platform 200 of FIG. 2) includes the communication system210, the in-flight data storage 220, the post-flight data storage 230,the data manager 250, the data retention policy engine 251, the datawarehouse 260, the data retention policy 252, and the platformoperations system 270, and the account holder system 280. In someimplementations, the platform operations system 270 is external to thecommunication platform. In some implementations, the data warehousesystem 260 is external to the communication platform. In someimplementations, the data retention policy engine 251 is constructed toperform redaction, data classifying, data aggregating, and encrypting.In some implementations, the data warehouse system 260 is included in anaccount holder system (e.g., the account holder system 280), and thecommunication platform includes information to access data in the datawarehouse system 260.

2. Multi-Tenant Computing Platform System

As shown in FIG. 3, a multi-tenant computing platform system 300includes a computing system 310, an in-flight data storage system 320, apost-flight data storage system 330, a data manager 350, a dataretention policy engine 351, a data warehouse system 360, and a platformoperations system 370. The account holder system 380 is external to thecomputing platform 300. The computing system 310 includes an accountingsystem 312, a data retention policy API 313, and a computing service API314.

In some implementations, the computing platform system 300 includes theaccount holder system. In some implementations, the platform operationssystem is external to the computing platform system. In someimplementations, the data warehouse system is external to the computingplatform system. In some implementations, the data retention policyengine is constructed to perform redaction, data classifying, dataaggregating, and encrypting. In some implementations, the data warehousesystem is included in an account holder system (e.g., the account holdersystem 380), and the computing platform system includes information toaccess data in the data warehouse system.

In some implementations, the computing platform system 300 is similar tothe computing platform described above for FIG. 1. In someimplementations, the in-flight data storage system 320 is similar to thein-flight data storage 220 of FIG. 2. In some implementations, thepost-flight data storage system 330 is similar to the post-flight datastorage 230 of FIG. 2. In some implementations, the data manager 350 issimilar to the data manager 250 of FIG. 2. In some implementations, thedata retention policy engine 351 is similar to the data retention policyengine 251 of FIG. 2. In some implementations, the data warehouse system360, is similar to the data warehouse system 260 of FIG. 2. In someimplementations, the platform operations system 370 is similar to theplatform operations system 270 of FIG. 2.

The system 300 is communicatively coupled to the external system 380 viathe data retention policy API 313 and the computing service API 314 ofthe computing system 310.

In the embodiment of FIG. 3, the external system 380 is a system of anaccount holder of an account (e.g., an account of the account system312) of the computing platform system 300. In some implementations,external systems include a system of an application developer thatprovides an application to users of the external system. In someimplementations, external systems include a system of a service providerthat provides a service to users of the external system. In someimplementations, external systems include a communication endpoint.

In some implementations, the computing system 310, the in-flight datastorage system 320, the post-flight data storage system 330, the datamanager 350, the data retention policy engine 351, the data warehousesystem 360, and the platform operations system 370 are implemented as aserver device. In some implementations, the computing system 310, thein-flight data storage system 320, the post-flight data storage system330, the data manager 350, the data retention policy engine 351, thedata warehouse system 360, and the platform operations system 370 areimplemented as a plurality of server devices communicatively coupled toeach other (e.g., a computing cluster).

The computing system 310 functions to provide any suitable computingservice (e.g., a service provided via the computing service API 314).

In some implementations, the computing system 310 includes an accountsystem (e.g., 312), which functions to allow distinct accounts to usethe computing system 310. An account is preferably operated by adeveloper or application provider that builds an application or servicethat utilizes the computing system 310. For example, in animplementation in which the computing system 310 is a communicationsystem, an account holder of an account may build a call centerapplication that uses the computing system 310 to direct customers tocustomer service representatives. Alternatively, the account holder ofan account may be an end user of an endpoint (e.g., phone number or SIPaddress) that uses the computing system 310 to provide some service. Forexample, an end user may use the computing system 310 to dynamicallydirect incoming calls to ring multiple destinations until the firstdevice picks up. Any suitable account hierarchy or division may be used.For example, an account may include subaccounts, which run differentinstances of an application with unique configuration. The accountsadditionally have specific authentication credentials. API requests andcommunication is preferably scoped to a particular account. Accordingly,a data retention policy provided by one account can be stored andassociated with the account.

The data retention policy API 313 is preferably a set of data retentionpolicy API calls and/or resources that can be used in the setting,editing, and reading of one or more data retention policies. In someimplementations, an account is preferably limited with privileges tointeracting with data retention policies associated with the account.

The data retention policy API 313 is preferably part of a RESTful APIbut may alternatively be any suitable API such as SOAP or customprotocol. The RESTful API works according to an HTTP request andresponse model. HTTP requests (or any suitable request communication) tothe computing platform 300 preferably observe the principles of aRESTful design. RESTful is understood in this document to describe aRepresentational State Transfer architecture as is known in the art. TheRESTful HTTP requests are preferably stateless, thus each messagecommunicated contains all necessary information for processing therequest and generating a response. The API service can include variousresources, which act as API endpoints, which act as a mechanism forspecifying requested information or requesting particular actions. Theresources can be expressed as URI's or resource paths. The RESTful APIresources can additionally be responsive to different types of HTTPmethods such as GET, PUT, POST and/or DELETE.

3. Method of FIG. 4

The method 400 of FIG. 4 includes setting a data retention policy (e.g.,352 of FIG. 3) of an account (e.g., an account of the account holdersystem 380) at the computing platform system (e.g., the system 300)(process S410); generating data (e.g., the original data 340) throughoperation of the computing platform system (e.g., 300) on behalf of theaccount (process S420); moderating the generated data of the accountaccording to the data retention policy of the account (process S430);and storing the moderated data (e.g., the policy compliant data 354 ofFIG. 3) (process S440). The computing platform system moderates thegenerated data by: securing sensitive information of the generated data(e.g., 340) from access by the computing platform system (e.g., 300);and providing operational information from the generated data, theoperational information being accessible by the computing platformsystem (e.g., 300) during performance of system operations (e.g., by theplatform operations system 370).

In some implementations, the moderated data is stored at a datawarehouse system (e.g., 360 of FIG. 3).

In some implementations, the method 400 includes: accessing, at thecomputing platform system (e.g., 300) (e.g., by using the platformoperations system 370) the moderated data (e.g., 354) stored at the datawarehouse system (e.g., 360) (process S450); and performing (e.g., byusing the platform operations system 370) at least one system operationby using the accessed moderated data (process S460). In someimplementations, system operations include at least one of usageanalytics, business intelligence operations, infrastructure scalingoperations, metering account usage, billing for account usage, frauddetection, error detection, general event pattern detection, platformadministration operations, allocating resources, deallocating resources,cluster management operations, and auditing operations.

In some implementations, the multi-tenant computing platform system 300performs the processes S410-S440. In some implementations, themulti-tenant computing platform system 300 performs the process S450. Insome implementations, the multi-tenant computing platform system 300performs the process S460.

In some implementations, the computing system 310 performs the processS410. In some implementations, the policy API 313 performs the processS410. In some implementations, the computing system 310 and the policyAPI 313 perform the process S410. In some implementations, the computingsystem 310 performs the process S410 responsive to a request receivedvia the policy API 313. In some implementations, the computing system310 performs the process S410 responsive to a response received via thepolicy API 313.

In some implementations, the computing system 310 performs the processS420.

In some implementations, the data retention policy engine 351 performsthe process S430.

In some implementations, the data retention policy engine 351 performsthe process S440. In some implementations, the data warehouse system 360performs the process S440. In some implementations, the system 300stores the moderated data (e.g., the moderated data 354 of FIG. 3) in astorage device (e.g., the storage medium 605 of FIG. 6) of the system300.

In some implementations, the system 300 stores the data retention policy(e.g., the data retention policy 352 of FIG. 3) in a storage device(e.g., the storage medium 605 of FIG. 6) of the system 300.

In some implementations, the platform operations system 370 performs theprocess S450. In some implementations, the platform operations system370 performs the process S460.

In some implementations, the process S410 is similar to the process S110of FIG. 1. In some implementations, the process S420 is similar to theprocess S120 of FIG. 1. In some implementations, the process S430 issimilar to the process S130 of FIG. 1. In some implementations, and theprocess S440 is similar to the process S140 of FIG. 1.

3.1 Setting a Data Retention Policy

In some implementations, the process S410 functions to control themulti-tenant computing platform system 300 to set a data retentionpolicy of an account (e.g., an account of the account system 312) at thecomputing platform system 300. In some implementations, the dataretention policy is set as described above for S110 of FIG. 1. In someimplementations, the data retention policy is similar to at least one ofthe data retention policies described above for S110 of FIG. 1.

In some implementations, the computing system 310 receives the dataretention policy (e.g., 352) in a data retention policy message providedby an external system (e.g., the external account holder system 380),and responsive to the data retention policy message, the computingsystem 310 sets the data retention policy (e.g., 352) at the system 300in association with an account identifier specified by the dataretention policy message (e.g., an account of the account holder system380). In some implementations, the computing system 310 receives thedata retention policy (e.g., 352) via the data retention policy API 313.

In some implementations, the computing system 310 receives the dataretention policy (e.g., 352) via an administrator control panel userinterface provided by the system 300 (e.g., provided to the externalaccount holder system 380).

In some implementations, the computing system 310 accesses aconfiguration file provided by an external account holder system (e.g.,380), and the configuration file defines the data retention policy 352.

In some implementations, the computing system 310 receives the dataretention policy (e.g., 352) by processing a configuration file. In someimplementations, the computing system 310 receives the data retentionpolicy (e.g., 352) by processing a configuration file of an accountholder of an account at the system 300 (e.g., an account associated withthe external system 380).

In some implementations, the data retention policy is specifiedon-demand. In some implementations, the data retention policy is definedin directives during operation of the computing system 310. Thecomputing system 310 processes such directives which set the dataretention policy at the system 300.

In some implementations in which the system 300 is a communicationplatform system, the data retention policy is selectively changed forpart or all of a call, as described above for S110. In someimplementations in which the system 300 is a communication platformsystem, the data retention policy is selectively changed at least aportion of a communication session (e.g., a telephony voicecommunication) in a manner similar to that which is described above forS110.

In some implementations, the data retention policy (e.g., 352) isreceived from an external account holder system (e.g., 380), and thepolicy is received with a request to apply the policy to one or morespecified data elements. In some implementations, specific data recordsare selectively targeted for particular data retention policycompliance. In some implementations, the data retention policy is atransformative data retention policy as described above for S110. Insome implementations, the data retention policy is a transformative dataretention policy that secures sensitive information while providing thesystem 300 with information for performing data-driven systemoperations. In some implementations, the transformative data retentionpolicy defines at least one data retention action to be performed on thedata during moderation of the data. In some implementations, thetransformative data retention policy defines at least one data retentionaction to be performed on the data during moderation of the data, and atleast one temporal property (e.g., a temporal property as describedabove for S110).

In some implementations, the computing system 310 sets the dataretention policy by storing the data retention policy 352 in a storagemedium of the system 300 (e.g., the storage medium 605 of FIG. 6) inassociation with the account identifier of the data retention policymessage. In some implementations, the computing system 310 sets the dataretention policy by storing the data retention policy 352 and theaccount identifier in a data retention policy data structure of thestorage medium of the system 300 (e.g., the storage medium 605 of FIG.6). In some implementations, the computing system 310 sets the dataretention policy by storing a data retention policy data structure ofthe storage medium of the system 300 (e.g., the storage medium 605 ofFIG. 6), the data retention policy data structure including the accountidentifier and a link to a storage location of the data retention policy352.

3.2 Generating the Data

In some implementations, the process S420 functions to control themulti-tenant computing platform system 300 to generate data (e.g., theoriginal data 340) through operation of the computing platform system(e.g., 300) on behalf of the account (e.g., an account of the accountsystem 312). In some implementations, the process S420 functions togenerate data within the system 300. In some implementations, thegenerated data (e.g., 340) is data that is produced as a result ofaccounts (of the system 300), users or other entities using themulti-tenant computing platform system 300.

In some implementations, the computing system 310 generates the data(e.g., the data 340) responsive to a computing request (e.g., thecomputing request 311) provided by an external system (e.g., the accountholder system 380) and received by the computing system 310 via thecomputing service API (Application Program Interface) 314.

In some implementations, the generated data includes at least one ofdata logs, API request records, API response records, captured packets,form data input, user generated data, generated media, and obtainedmedia.

The data is similar to the generated data described above for S120 ofFIG. 1).

3.3 Moderating the Generated Data

In some implementations, the process S430 functions to control themulti-tenant computing platform system 300 to moderate the generateddata of the account according to the data retention policy of theaccount. In some implementations, the data manger 350 receives thegenerated data (e.g., 340) from the computing system 310. In someimplementations, the data manger 350 receives the generated data (e.g.,340) from the in-flight data storage system 320. In someimplementations, the data manger 350 receives the generated data (e.g.,340) from the post-flight data storage system 330.

In some implementations, the data manager 350 moderates the receivedgenerated data according to the data retention policy 352. In someimplementations, the data retention policy engine 351 of the data manger350 moderates the received generated data according to the dataretention policy 352. In some implementations, the data manager 350receives the policy 352 from the computing system 310. In someimplementations, the data manager 350 receives the policy 352 from anexternal system (e.g., the external account holder system 380). In someimplementations, the data manager 350 moderates the data as describedfor S130 of FIG. 1.

In some implementations, the data retention policy engine 351 stores thedata retention policy 352. In some implementations, the data retentionpolicy engine 351 manages the data retention policy 352.

In some implementations, the data manager 350 moderates the receivedgenerated data by performing actions defined by the data retentionpolicy 352. In some implementations, actions include at least one ofdata redaction, data censoring, data classifying, data bucketing, dataaggregating, data encryption, and partial deletion.

In some implementations, the data retention policy (e.g., 352) definesactions performed by the computing platform system 300 on the data(e.g., 340) to secure the sensitive information prior to storing thedata in a data warehouse (e.g., 360) of the computing platform system,and moderating data includes performing the actions defined by the dataretention policy. In some implementations, actions include at least oneof data redaction, data censoring, data classifying, data bucketing,data aggregating, data encryption, and partial deletion.

In some implementations, the data manager 350 performs redaction asdescribed above for S130 of FIG. 1. In some implementations, dataredaction includes automatically detecting and removing at least one ofa credit card number, social security number, account number, andaddress from the data (e.g., 340).

In some implementations, the data manager 350 performs data classifyingas described above for S130 of FIG. 1. In some implementations, dataclassifying includes replacing data with a generalized representation ofthe data.

In some implementations, the data manager 350 performs data aggregatingas described above for S130 of FIG. 1. In some implementations, dataaggregating includes replacing metrics of data with an aggregatedrepresentation of the metrics of data.

In some implementations, the data manager 350 performs data encryptionas described above for S130 of FIG. 1. In some implementations, dataencryption includes determining an encryption callback reference (e.g.,381) for the data, transmitting the data to an external system (e.g.,380) of the encryption callback reference (e.g., 381), and replacing thedata (e.g., the original data 340) with encrypted data provided by theexternal system of the encryption callback reference, wherein theaccount is an account for the external system (e.g., 380). In someimplementations, the encryption allows only an account holder of theaccount (e.g., an account of the accounting system 312 that correspondsto the data retention policy) to access the encrypted sensitiveinformation.

In some implementations, the data manager 350 performs partial deletionas described above for S130 of FIG. 1.

In some implementations, the data manager 350 moderates the receivedgenerated data 340 after active use of the generated data by thecomputing system 310, and prior to long term storage of the data (e.g.,in the data warehouse 360). In some implementations, the data manager350 moderates newly generated data (e.g., 340) at a periodic interval.In some implementations, the data manager 350 moderates newly generateddata (e.g., 340) immediately as the data is generated.

In some implementations, moderating the generated data (process S430)includes securing sensitive information of the generated data (e.g.,340) from access by the computing platform system (e.g., 300); andproviding operational information from the generated data, theoperational information being accessible by the computing platformsystem (e.g., 300) during performance of system operations (e.g., by theplatform operations system 370). In some implementations, the datamanager 350 secures sensitive information of the generated data. In someimplementations, the data retention policy engine 351 secures sensitiveinformation of the generated data. In some implementations, the datamanager 350 provides the operational information from the generateddata. In some implementations, the data retention policy engine 351provides the operational information from the generated data.

In some implementations, securing sensitive information includes atleast one of redacting, removing, censoring and encrypting of thesensitive information of the generated data. In some implementations,the encrypting is performed by using an external system (e.g., theexternal account holder system 380) associated with the account (e.g.,an account of the accounting system 312), and the encrypted sensitiveinformation is secured from access by the computing platform system(e.g., 300).

In some implementations, providing operation information from thegenerated data includes at least one of: preserving operationalinformation from the generated data, providing a portion of thegenerated data as operation information, and generating operationinformation from the generated data.

In some implementations, providing a portion of the generated dataincludes performing redaction on at least one portion of the generateddata, preserving at least one portion of the original data, andproviding each preserved portion for storage (e.g., providing eachpreserved portion to the data warehouse 360). In some implementations,providing a portion of the generated data includes performing datadeletion on at least one portion of the generated data, preserving atleast one portion of the original data, and providing each preservedportion for storage (e.g., providing each preserved portion to the datawarehouse 360). In some implementations, providing a portion of thegenerated data includes performing data encryption on at least oneportion of the generated data, preserving at least one portion of theoriginal data in an unencrypted format, and providing each preserved(unencrypted) portion for storage (e.g., providing each preservedportion to the data warehouse 360).

In some implementations, generating operation information from thegenerated data includes performing a data classification process asdescribed above for S130 of FIG. 1, and providing data classificationsgenerated by the classification process as the operation information. Insome implementations, generating operation information from thegenerated data includes performing a data aggregation process asdescribed above for S130 of FIG. 1, and providing aggregated datagenerated by the aggregation process as the operation information.

In some implementations, system operations (e.g., performed by theplatform operations system 370) include at least one of usage analytics,business intelligence operations, infrastructure scaling operations,metering account usage, billing for account usage, fraud detection,error detection, general event pattern detection, platformadministration operations, allocating resources, deallocating resources,cluster management operations, and auditing operations.

3.4 Storing the Moderated Data

In some implementations, the process S440 functions to control themulti-tenant computing platform system 300 to store the moderated data(e.g., the policy compliant data 354 of FIG. 3). In someimplementations, the system 300 stores the moderated data at the datawarehouse 360. In some implementations, the system 300 stores themoderated data at a log file storage location of the system 300 (e.g., astorage location of the storage medium 605 of FIG. 6). In someimplementations, the system 300 stores the moderated data at a mediarecords storage location of the system 300 (e.g., a storage location ofthe storage medium 605 of FIG. 6).

3.5 Accessing the Moderated Data

In some implementations, the process S450 functions to control themulti-tenant computing platform system 300 to access the storedmoderated data. In some implementations, the platform operations system370 accesses the stored moderated data. In some implementations, themoderated data is accessed at the data warehouse system 360. In someimplementations, the moderated data is accessed at a log file storagelocation of the system 300. In some implementations, the moderated datais accessed at a media records storage location of the system 300

3.6 Performing System Operations

In some implementations, the process S460 functions to control themulti-tenant computing platform system 300 perform at least one systemoperation by using the accessed moderated data. In some implementations,the platform operations system 370 performs at least one systemoperation by using the accessed moderated data. In some implementations,system operations include at least one of usage analytics, businessintelligence operations, infrastructure scaling operations, meteringaccount usage, billing for account usage, fraud detection, errordetection, general event pattern detection, platform administrationoperations, allocating resources, deallocating resources, clustermanagement operations, and auditing operations.

4. Method of FIG. 5

The method 500 of FIG. 5 includes: moderating original data (e.g., 340)generated through operation of the computing platform system (e.g.,generated through operation of the computing system 310) on behalf of anaccount (e.g., an account of the account system 312) of the computingplatform system, the moderating being performed according to a dataretention policy (e.g., 352) set for the account (process S510); andstoring the moderated data (e.g., 354) at the computing platform system(process S520). The computing platform system (e.g., 300) moderates thegenerated data (e.g., 340) by: securing sensitive information of thegenerated data (e.g., 340) from access by the computing platform system(e.g., 300); and providing operational information from the generateddata, the operational information being accessible by the computingplatform system (e.g., 300) during performance of system operations(e.g., by the platform operations system 370).

In some implementations, the moderated data is stored at a datawarehouse system (e.g., 360 of FIG. 3).

In some implementations, the method 500 includes: accessing, at thecomputing platform system (e.g., 300) (e.g., by using the platformoperations system 370) the moderated data (e.g., 354) stored at the datawarehouse system (e.g., 360) (process S530); and performing (e.g., byusing the platform operations system 370) at least one system operationby using the accessed moderated data (process S540). In someimplementations, system operations include at least one of usageanalytics, business intelligence operations, infrastructure scalingoperations, metering account usage, billing for account usage, frauddetection, error detection, general event pattern detection, platformadministration operations, allocating resources, deallocating resources,cluster management operations, and auditing operations.

In some implementations, the multi-tenant computing platform system 300performs the processes S510-S520. In some implementations, themulti-tenant computing platform system 300 performs the process S530. Insome implementations, the multi-tenant computing platform system 300performs the process S540.

In some implementations, the data retention policy engine 351 performsthe process S510. In some implementations, the data manager 350 performsthe process S510

In some implementations, the data retention policy engine 351 performsthe process S520. In some implementations, the data warehouse system 360performs the process S520. In some implementations, the system 300stores the moderated data (e.g., the moderated data 354 of FIG. 3) in astorage device (e.g., the storage medium 605 of FIG. 6) of the system300.

In some implementations, the method of FIG. 5 is similar to the methodof FIG. 4. In some implementations, process S510 is similar to theprocess S430 of FIG. 4. In some implementations, process S520 is similarto the process S440 of FIG. 4. In some implementations, process S530 issimilar to the process S450 of FIG. 4. In some implementations, processS540 is similar to the process S460 of FIG. 4.

In some implementations, the data retention policy is set for theaccount as described above for the process S410 of FIG. 4. In someimplementations, the original data is generated as described above forthe process S420.

In some implementations, the data retention policy (e.g., 352) definesactions performed by the computing platform system 300 on the data(e.g., 340) to secure the sensitive information prior to storing thedata in a data warehouse (e.g., 360) of the computing platform system,and moderating data includes performing the actions defined by the dataretention policy.

In some implementations, the data (e.g., 340) includes at least one ofdata logs, API request records, API response records, captured packets,form data input, user generated data, generated media, and obtainedmedia.

In some implementations, actions include at least one of data redaction,data censoring, data classifying, data bucketing, data aggregating, dataencryption, and partial deletion.

In some implementations, data redaction includes automatically detectingand removing at least one of a credit card number, social securitynumber, account number, and address from the data (e.g., 340). In someimplementations, data classifying includes replacing data with ageneralized representation of the data. In some implementations, dataaggregating includes replacing metrics of data with an aggregatedrepresentation of the metrics of data. In some implementations, dataencryption includes determining an encryption callback reference (e.g.,381) for the data, transmitting the data to an external system (e.g.,380) of the encryption callback reference, and replacing the data withencrypted data provided by the external system of the encryptioncallback reference, wherein the account is an account for the externalsystem (e.g., 380).

In some implementations, the computing platform system (e.g., 300)secures the sensitive information from access by the computing platformsystem (e.g., 300) by performing at least one of removing, censoring andencrypting of the sensitive information of the generated data. In someimplementations, the computing platform system provides the operationalinformation from the generated data by at least one of preservingoperational information from the generated data and generating operationinformation from the generated data. In some implementations, theencrypting is performed by using an external system (e.g., 380)associated with the account, and the encrypted sensitive information issecured from access by the computing platform system (e.g., 300).

In some implementations, the encryption allows only an account holder ofthe account to access the encrypted sensitive information.

In some implementations, system operations include at least one of usageanalytics, business intelligence operations, infrastructure scalingoperations, metering account usage, billing for account usage, frauddetection, error detection, general event pattern detection, platformadministration operations, allocating resources, deallocating resources,cluster management operations, and auditing operations. In someimplementations, system operations include at least one of meteringaccount usage, and billing for account usage.

In some implementations, the computing platform system performs at leastone system operation by using the operational information. In someimplementations, the computing platform system performs at least onesystem operation by using the stored moderated data. In someimplementations, the moderated data is stored at a data warehouse system(e.g., 360), and the computing platform system accesses the moderateddata stored at the data warehouse system and performs at least onesystem operation by using the accessed moderated data.

5. System Architecture: Computing Platform System

FIG. 6 is an architecture diagram of a system (e.g., the computingplatform system 300 of FIG. 3) according to an implementation in whichthe system is implemented by a server device. In some implementations,the system is implemented by a plurality of devices. In someimplementations, the system 300 is similar to the communication platform200 of FIG. 2.

The bus 601 interfaces with the processors 601A-601N, the main memory(e.g., a random access memory (RAM)) 622, a read only memory (ROM) 604,a processor-readable storage medium 605, a display device 607, a userinput device 608, and a network device 611.

The processors 601A-601N may take many forms, such as ARM processors,X86 processors, and the like.

In some implementations, the system (e.g., 600) includes at least one ofa central processing unit (processor) and a multi-processor unit (MPU).

The processors 601A-601N and the main memory 622 form a processing unit699. In some embodiments, the processing unit includes one or moreprocessors communicatively coupled to one or more of a RAM, ROM, andmachine-readable storage medium; the one or more processors of theprocessing unit receive instructions stored by the one or more of a RAM,ROM, and machine-readable storage medium via a bus; and the one or moreprocessors execute the received instructions. In some embodiments, theprocessing unit is an ASIC (Application-Specific Integrated Circuit). Insome embodiments, the processing unit is a SoC (System-on-Chip). In someembodiments, the processing unit includes one or more of a computingsystem, a data manager, a data warehouse, a platform operations system,an in-flight data storage system, a post-flight data storage system, adata retention policy storage system, at least one data retentionpolicy, in-flight data, and post-flight data.

The network adapter device 611 provides one or more wired or wirelessinterfaces for exchanging data and commands between the system (e.g.,600) and other devices, such as an external system (e.g., 380). Suchwired and wireless interfaces include, for example, a universal serialbus (USB) interface, Bluetooth interface, Wi-Fi interface, Ethernetinterface, near field communication (NFC) interface, and the like.

Machine-executable instructions in software programs (such as anoperating system, application programs, and device drivers) are loadedinto the memory 622 (of the processing unit 699) from theprocessor-readable storage medium 605, the ROM 604 or any other storagelocation. During execution of these software programs, the respectivemachine-executable instructions are accessed by at least one ofprocessors 601A-601N (of the processing unit 699) via the bus 601, andthen executed by at least one of processors 601A-601N. Data used by thesoftware programs are also stored in the memory 622, and such data isaccessed by at least one of processors 601A-601N during execution of themachine-executable instructions of the software programs. Theprocessor-readable storage medium 605 is one of (or a combination of twoor more of) a hard drive, a flash drive, a DVD, a CD, an optical disk, afloppy disk, a flash storage, a solid state drive, a ROM, an EEPROM, anelectronic circuit, a semiconductor memory device, and the like. Theprocessor-readable storage medium 605 includes machine-executableinstructions (and related data) for an operating system 612, softwareprograms 613, device drivers 614, the computing system 310, thein-flight data storage system 320, the post-flight data storage system330, the data manager 350, and the platform operations system 370. Insome implementations, the processor-readable storage medium 605 includesmachine-executable instructions (and related data) for the datawarehouse 360. In some implementations, the data warehouse is externalto the system 300. In some implementations, the platform operationssystem is external to the system 300.

In some implementations, the processor-readable storage medium 605includes in-flight data. In some implementations, the processor-readablestorage medium 605 includes post-flight data. In some implementations,the processor-readable storage medium 605 includes the policy compliant(moderated) data 354. In some implementations, the processor-readablestorage medium 605 includes data retention policies 615 of a pluralityof accounts of the system 300 (e.g., accounts of the account system 312of FIG. 3). In some implementations, the processor-readable storagemedium 605 includes the data retention policy 352.

6. Machines

The systems and methods of the preferred embodiments and variationsthereof can be embodied and/or implemented at least in part as a machineconfigured to receive a computer-readable medium storingcomputer-readable instructions. The instructions are preferably executedby computer-executable components preferably integrated with thecomputing platform. The computer-readable medium can be stored on anysuitable computer-readable media such as RAMs, ROMs, flash memory,EEPROMs, optical devices (CD or DVD), hard drives, floppy drives, or anysuitable device. The computer-executable component is preferably ageneral or application specific processor, but any suitable dedicatedhardware or hardware/firmware combination device can alternatively oradditionally execute the instructions.

6. Conclusion

As a person skilled in the art will recognize from the previous detaileddescription and from the figures and claims, modifications and changescan be made to the preferred embodiments of the invention withoutdeparting from the scope of this invention defined in the followingclaims.

What is claimed is:
 1. A method, comprising: at a hardware data managersystem: securing sensitive information of original data from access by acomputing platform system that generates the original data, the originaldata being generated by the platform system through operation of theplatform system on behalf of a platform account of the platform system,the data manager system securing the sensitive information according toa data retention policy set for the platform account, and providingoperational information from the generated data, the operationalinformation being accessible by the computing platform system duringperformance of system operations.
 2. The method of claim 1, wherein thecomputing platform system is a multi-tenant computing platform system.3. The method of claim 2, wherein the data retention policy definesactions to secure the sensitive information, and wherein securingsensitive information comprises performing the actions defined by thedata retention policy.
 4. The method of claim 2, wherein the dataincludes at least one of data logs, API request records, API responserecords, captured packets, form data input, user generated data,generated media, and obtained media.
 5. The method of claim 2, whereinactions include at least one of data redaction, data censoring, dataclassifying, data bucketing, data aggregating, data encryption, andpartial deletion.
 6. The method of claim 2, wherein system operationsinclude at least one of usage analytics, business intelligenceoperations, infrastructure scaling operations, metering account usage,billing for account usage, fraud detection, error detection, generalevent pattern detection, platform administration operations, allocatingresources, deallocating resources, cluster management operations, andauditing operations.
 7. The method of claim 2, wherein data managersystem receives the data retention policy in a data retention policymessage provided by an external system, and the data retention policy isassociated with an account identifier specified by the data retentionpolicy message, the account identifier being an account identifier ofthe platform account.
 8. The method of claim 2, wherein the dataretention policy is received from an external account holder system, andthe data retention policy is received with a request to apply the dataretention policy to one or more specified data elements.
 9. The methodof claim 2, wherein the computing platform system is a multi-tenanttelephony communication platform system, and wherein the data isgenerated responsive to execution of a communication on thecommunication platform system.
 10. The method of claim 1, wherein thedata manager system secures the sensitive information from access by thecomputing platform system by performing at least one of removing,censoring and encrypting of the sensitive information, wherein the datamanager system provides the operational information from the generateddata by at least one of preserving operational information from thegenerated data and generating operation information from the generateddata, and wherein the data manager system performs the encrypting byusing an external system associated with the platform account, and theencrypted sensitive information is secured from access by the computingplatform system.
 11. A hardware data manager system comprising: a dataretention policy engine constructed to: secure sensitive information oforiginal data from access by a computing platform system that generatesthe original data, the original data being generated by the platformsystem through operation of the platform system on behalf of a platformaccount of the platform system, the data retention policy enginesecuring the sensitive information according to a data retention policyset for the platform account, and provide operational information fromthe generated data, the operational information being accessible by thecomputing platform system during performance of system operations. 12.The data manager system of claim 11, wherein the computing platformsystem is a multi-tenant computing platform system.
 13. The data managersystem of claim 12, wherein the data retention policy defines actions tosecure the sensitive information, and wherein the data retention policyengine is constructed to secure sensitive information by performing theactions defined by the data retention policy.
 14. The data managersystem of claim 12, wherein the data includes at least one of data logs,API request records, API response records, captured packets, form datainput, user generated data, generated media, and obtained media.
 15. Thedata manager system of claim 12, wherein actions include at least one ofdata redaction, data censoring, data classifying, data bucketing, dataaggregating, data encryption, and partial deletion.
 16. The data managersystem of claim 12, wherein system operations include at least one ofusage analytics, business intelligence operations, infrastructurescaling operations, metering account usage, billing for account usage,fraud detection, error detection, general event pattern detection,platform administration operations, allocating resources, deallocatingresources, cluster management operations, and auditing operations. 17.The data manager system of claim 12, wherein data retention policyengine is constructed to receive the data retention policy in a dataretention policy message provided by an external system, wherein thedata retention policy is associated with an account identifier specifiedby the data retention policy message, and wherein the account identifieris an account identifier of the platform account.
 18. The data managersystem of claim 12, wherein the data retention policy engine isconstructed to receive the data retention policy from an externalaccount holder system, and wherein the data retention policy is receivedwith a request to apply the data retention policy to one or morespecified data elements.
 19. The data manager system of claim 12,wherein the computing platform system is a multi-tenant telephonycommunication platform system, and wherein the data is generatedresponsive to execution of a communication on the communication platformsystem.
 20. The data manager system of claim 11, wherein the dataretention policy engine is constructed to secure the sensitiveinformation from access by the computing platform system by performingat least one of removing, censoring and encrypting of the sensitiveinformation, wherein the data retention policy engine is constructed toprovide the operational information from the generated data by at leastone of preserving operational information from the generated data andgenerating operation information from the generated data, and whereinthe data retention policy engine is constructed to perform theencrypting by using an external system associated with the platformaccount, and wherein the encrypted sensitive information is secured fromaccess by the computing platform system.